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10.1007/s12561-016-9151-2 http://scihub22266oqcxt.onion/10.1007/s12561-016-9151-2 C5087812!5087812 !27812370     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\27812370 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Stat+Biosci 2016 ; 2016 (ä): 1-17 Nephropedia Template TP {{tp|p=27812370 |t=2016. Post-GWAS Prioritization Through Data Integration Provides Novel Insights on Chronic Obstructive Pulmonary Disease |pdf=|usr=}}{{27812370 }} gab.com Text Post-GWAS Prioritization Through Data Integration Provides Novel Insights on Chronic Obstructive Pulmonary Disease JO: Stat Biosci http://www.kidney.de/pget.php?&tw=1&pmid=27812370 #FOAvip Rich collections of genomic and epigenomic annotations, availabilities of large population cohorts for genome-wide association studies (GWAS), and advancements in data integration techniques provide the unprecedented opportunity to accelerate discoveries in complex disease studies through integrative analyses. In this paper, we apply a variety of approaches to integrate GWAS summary statistics of chronic obstructive pulmonary disease (COPD) with functional annotations to illustrate how data integration could help researchers understand complex human diseases. We show that incorporating functional annotations can better prioritize GWAS signals at both the global and the local levels. Signal prioritization on severe COPD GWAS reveals multiple potential risk loci that are linked with pulmonary functions. Enrichment analysis provides novel insights on the pathogenesis of COPD and hints the existence of genetic contributions to muscle dysfuncion and chronic lung inflammation, two symptoms that are often co-morbid with COPD. Our results suggest that rich signals for COPD genetics are still buried under the Bonferroni-corrected genome-wide significance threshold. Many more biological findings are expected to emerge as more samples are recruited for COPD studies. Twit Text FOAVip Post-GWAS Prioritization Through Data Integration Provides Novel Insights on Chronic Obstructive Pulmonary Disease ????Stat Biosci http://www.kidney.de/pget.php?&tw=1&pmid=27812370 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27812370 #FOAvip English Wikipedia <ref>{{Cite pmid|27812370 }}</ref> Post-GWAS Prioritization Through Data Integration Provides Novel Insights on Chronic Obstructive Pulmonary Disease #MMPMID27812370 Lu Q ; Jin C ; Sun J ; Bowler R ; Kechris K ; Kaminski N ; Zhao H Stat Biosci 2016[]; 2016 (ä): 1-17 PMID27812370 show ga Rich collections of genomic and epigenomic annotations, availabilities of large population cohorts for genome-wide association studies (GWAS), and advancements in data integration techniques provide the unprecedented opportunity to accelerate discoveries in complex disease studies through integrative analyses. In this paper, we apply a variety of approaches to integrate GWAS summary statistics of chronic obstructive pulmonary disease (COPD) with functional annotations to illustrate how data integration could help researchers understand complex human diseases. We show that incorporating functional annotations can better prioritize GWAS signals at both the global and the local levels. Signal prioritization on severe COPD GWAS reveals multiple potential risk loci that are linked with pulmonary functions. Enrichment analysis provides novel insights on the pathogenesis of COPD and hints the existence of genetic contributions to muscle dysfuncion and chronic lung inflammation, two symptoms that are often co-morbid with COPD. Our results suggest that rich signals for COPD genetics are still buried under the Bonferroni-corrected genome-wide significance threshold. Many more biological findings are expected to emerge as more samples are recruited for COPD studies. äPost-GWAS Prioritization Through Data Integration Provides Novel Insig(epmc).pdf DeepDyve Pubget Overpricing